Engines (or motors) are designed to convert one form of energy (such as, for example, fuel combustion, electricity, nuclear reactions, and the like) to mechanical energy, such as, for example, mechanical motion. For instance, combustion engines convert fuel combustion energy to motion energy. These engines typically include one or more combustion chambers that contain and confine the combustion of a fuel (e.g., a fossil fuel), allowing the resultant high temperature and high pressure gases to expand and drive mechanical components such as, for example, pistons, turbine blades, or the like.
Internal combustion engines are typically used in vehicles, including, e.g., motorcycles, scooters, automobiles, boats, trucks, locomotives, watercraft, aircraft, ships, gas turbines, generators, heavy duty machinery, and the like. During operation of, for example, an internal combustion engine that comprises one or more pistons, a piston may be driven by expanding gases resulting from the combustion of the fuel in the chamber, causing the piston to move along a predetermined path for a predetermined distance along a length of the chamber. The piston may be connected to a crankshaft through a connecting rod to translate the movement of the piston to a rotation of the crankshaft. The engine may further include an intake valve or port and an exhaust valve or port. The engine may comprise any number of sets of pistons, connecting rods and chambers. The various moving parts of the engine cause friction, which results in the wear of the moving parts and diminished power output of the engine.
Most of the moving parts in the engine are made of metal. During operation, metal to metal contact of the moving parts causes wear on the moving parts. To minimize wear of the moving parts, and, therefore, to maximize engine durability and longevity, a lubricant (e.g., an engine oil) is used to lubricate the moving parts in the engine. The lubricant may also function to clean, inhibit corrosion, improve sealing, and cool the engine by carrying heat away from the moving parts. The lubricant reduces friction by, for example, creating a separating film between surfaces of adjacent moving parts to minimize direct contact between the surfaces, decreasing heat caused by the friction and reducing wear.
Most lubricants are made from a petroleum hydrocarbon derived from crude oil. Alternatively (or additionally), the lubricants may be made from synthetic materials, such as, e.g., synthetic esters, polyalphaolefins, and the like. Additives are added to the lubricant to maintain or improve certain properties of the lubricant. The additives may include, for example, detergents, dispersants, corrosion inhibitors, alkaline additives, and the like. One of the most important properties of lubricants is to maintain a lubricating film between the moving parts of the engine. Another important property of lubricants is its ability to neutralize acids.
In engines, the lubricants are exposed to the byproducts of internal combustion, including, for example, carbonaceous particles, metallic particles, and the like. During operation of the engine, the lubricants undergo both thermal and mechanical degradation, and contamination which impairs their function. Eventually the loss of performance may become significant enough to necessitate removal of the used lubricant and replacement with a fresh lubricant. Thus, time-based (e.g., 92 days, 184 days, 276 days, every 6 months, or the like) and/or distance-based (e.g., every three thousand miles, every five thousand miles, or the like) lubricant drainage intervals (LDIs) are typically used in determining when to replace the lubricants in an engine.
In the railroad industry, engine oil samples are typically taken from locomotive engines about every 2 to 3 weeks. These samples are then analyzed to identify problems, such as, e.g., coolant leaks, fuel dilution, metal wear, oil deterioration, improper oil in use, and the like. The railroads schedule oil change intervals based on, e.g., original equipment manufacturer (OEM) recommendations, operating history, and the like. Currently, a common industry practice for drain intervals is about every 184 days. However, this drain interval may be too long for some engines, such as, e.g., engines that are operated under severe conditions, or engines that are experiencing performance issues, or new engines that have just been placed into service and are susceptible to break-in wear. Further, the time between drain intervals may be shorter than optimal for some engines, such as, e.g., engines that are operated under ideally optimal conditions. Also, new engines may require more frequent oil changes than older engines.
In the trucking industry, for example, truck fleets have often utilized oil analysis to establish oil drain intervals for entire fleets. The oil drain intervals, however, are based on fleets rather than individual engines. Again, the established oil drain intervals may be too long for some engines, while shorter than necessary for others.
While lubricant drainage intervals are typically set based on the time in service or the distance that a vehicle has traveled, actual operating conditions and engine hours of operation may vary drastically for a give time in service or a distance traveled by a vehicle. Thus, fixed time/distance lubricant discard (or drain) intervals may result in the continued use of spent engine lubricant where an engine is operated under severe conditions or where the engine is not operating properly, which may result in poor fuel efficiency, costly maintenance, premature engine failure, and the like. The fixed time/distance lubricant discard intervals may also result in the premature, and therefore, inefficient discarding of engine lubricant that remains unspent at the discard interval, thereby increasing the amount of waste byproduct to be disposed of, as well as the costs associated with the replacement of the engine lubricant (including, e.g., the cost of the lubricant, the cost of labor to replace the lubricant, disposal costs, engine down time costs, and the like).
The engine lubricant may be considered to be spent when, for example, the properties of the engine lubricant have been degraded to a point where the engine lubricant ceases to properly lubricate the engine parts, inhibit corrosion, or the like.
Although it would seem ideal to analyze the condition of used oil from each piece of equipment and only change it when the analysis indicates it is close to the end of its useful life, there are other costs to consider in determining the most cost effective time to change oil. In their use, engines contribute to revenue production making it costly to take them out of service. As a consequence many maintenance tasks for equipment are preplanned and grouped together enabling these tasks to be performed during a planned shutdown of the equipment, or when many of the tasks can be performed simultaneously to minimize downtime. Equipment operators usually schedule maintenance to optimize overall cost. This means that to maximize production, individual maintenance tasks may be performed before they are actually needed.
Some maintenance tasks need to be performed more frequently than others. Preplanned maintenance is often based around a set of schedules. For example a fleet of trucks may have an A schedule every 30 days, a B schedule every 60 days, and a C Schedule every 120 days. A truck coming in for its first maintenance after 30 days would have all the services performed that are required in Schedule A. 30 days later it would have services A and B performed. 30 days after that (90 days cumulative) it would require the services in schedule A only. At 120 days of service it would require all the procedures in schedules A, B and C. The cycle would then be repeated.
If the fleet oil drain interval was scheduled for 30 days, and it was determined that a 45 day oil change interval would be safe, it is highly unlikely that taking these trucks out of service at 45 days only to change oil would be a cost effective undertaking. Moving the fleet to a 60 day oil change would be a practical endeavor, if that was determined to be a safe drain interval, because it would convert the oil change from a schedule A to a schedule B function, cut the oil change costs in half, and not result in any new out of service costs. If the oil change happened to be the only item in maintenance schedule A, this would result in a productivity improvement because the equipment would be taken out of service less frequently.
Because it is often difficult to predict how much useful life remains in a used oil, oil change intervals are frequently standardized across like pieces of equipment in a business unit. The oil change interval selection can be based on many different factors including the business unit's maintenance history with the specific equipment, the severity of service, the equipment manufacturer's recommendation, used oil analysis, etc. The oil change interval is usually chosen by what the business unit believes is the lowest overall cost in the trade-off between maintenance costs, repair costs, and downtime. Because no two units are identical, or used in identical service, the oil change interval is usually chosen to accommodate the most severe situation. This means that in a set of like engines, some engines that are milder or in milder service, and may be able to operate quite effectively on longer oil drain intervals.
A good example is railroad locomotives. These engines require safety inspections every 92 days. Oil changes used to be performed every 92 days to coincide with this out of service point. Many locomotive fleets have found that conditions are such that they can now change oil every 184 days. The next logical oil change interval increase would be to 276 days to coincide with a safety inspection. Some locomotives, particularly some GE FDL units under some operating conditions, cannot safely go for 276 days without an oil change. Thus, an unfulfilled need exists for a system and method to test used oil and predict at, for example, 150 days of service, based on the used oil analysis, which units should be changed at, e.g., 184 days and which units can safely continue to, e.g., 276 days without an oil change.
The foregoing oil change intervals contemplate removing all of the used oil from the engine and replacing all of the used oil with fresh oil on a selected oil change interval. Methods for predicting such interval typically use a linear regression model to determine one or more oil parameters that are predicted to be exceeded at some future point in time. While such models may be useful for such predictions, there continues to be a need for a more accurate prediction model for determining a lubricant discard (or drain interval).
In view of the foregoing and other needs, the disclosure provides a system, a method, and a computer program for predicting a lubricant drain interval in an engine based on a plurality of analysis parameter values measured in a plurality of samples of used engine lubricant taken from the engine over a period of time. The system includes a first input that receives the plurality of analysis parameter values and a plurality of historical analysis parameter values for the engine that are indicative of one or more characteristics of the used lubricant and stores the plurality of analysis parameter values and historical analysis parameter values in a memory of a processor. A second input that receives an analysis parameter threshold value for the used lubricant at the end of a service interval is stored in the memory of the processor. A determiner determines a future analysis parameter value for determining the lubricant drain interval by performing modeling of the plurality of analysis parameter values and historical analysis parameter values, and comparing the future analysis parameter value to the analysis parameter threshold value to determine whether or not the future analysis parameter value exceeds (or is less than) the analysis parameter threshold value at the end of the service interval in order to provide an output indicating the lubricant discard (or drain) interval (LDI) in an engine. The modeling performed by the determiner is selected from a partial least squares regression model, a neural network model, a general linear model regression model, and the like.
The determiner may be configured to generate the lubricant drain interval for the engine. The determiner may perform modeling on the historical analysis parameter value and said analysis parameter value to determine the future analysis parameter value. The modeling may comprise: a neural network analysis, a general linear model regression analysis, a generalized linear model regression analysis, a principle components regression analysis, a partial least squares analysis; and the like. The determiner may compare the future analysis parameter value to the analysis parameter threshold value. The determiner may generate the lubricant drain interval for the engine based on the comparison of the future analysis parameter value to the analysis parameter threshold value for the lubricant.
The first input may receive an additional analysis parameter value, and the determiner may perform a neural network analysis, a general linear model regression analysis, a generalized linear model regression analysis, a principle components regression analysis, a partial least squares analysis; and the like on the additional analysis parameter value. The analysis parameter value may include, for example, oil pressure, megawatt hours produced, locomotive unit age, a concentration of iron in the engine lubricant sample and the additional analysis parameter value may include, for example, a concentration of lead in the engine lubricant sample. The analysis parameter value and the additional analysis parameter value may be selected, for example, from iron, lead, tin, copper aluminum, boron, oxidation, nitration, potassium, silicon, sodium, soot, TBN, water, fuel, sludge, and insolubles in the engine lubricant sample.
The analysis parameter m is selected, for example, from a group of analysis parameters consisting of iron, lead, tin, copper aluminum, boron, oxidation, nitration, potassium, silicon, sodium, soot, water, fuel, sludge, insolubles, etc.
In addition to “used lubricant analysis parameters” described above, it may be beneficial to include “non used lubricant parameters” in the predictive model to ascertain the appropriate LDI and the need for unit servicing. Some examples of non used lubricant parameters that may be included in the model for determining the LDI and their potential effects on the determination of the LDI may include, but are not limited to: (1) oil pressure, wherein a decrease in oil pressure may indicate a water leak and an increase in oil pressure may indicate that the oil viscosity or soot content of the oil is increasing; (2) run time hours of an engine or unit wherein an increase or decrease in nm time hours may affect the “aging” rate of the lubricant in the unit or engine; (3) engine temperature, wherein high temperature engine conditions may affect the oxidation rate and volatile content losses of the lubricant. Volatile content losses may result in a lubricant viscosity increase due to thickening of the lubricant in the engine; (4) megawatt hours produced, wherein units that produce comparatively high levels of power may increase the “aging” rate of the lubricant in the crankcase, while production of low levels of power may decrease the “aging” rate of the lubricant: (5) total miles of the unit or engine between oil changes, wherein units having higher or lower cumulative miles between oil changes may affect the “aging” rate of the lubricant in the engine; and (6) the age of the engine or unit, wherein engines or units that are relatively new may exhibit a higher metal content in the lubricant due to mating parts wearing or “breaking in” during the early life of the engine or unit. All of the foregoing parameters and relationships may be linear, non-linear, or interactive with one or more used oil analysis parameters.
The method may further comprise predicting a probability when the future analysis parameter value will exceed the analysis parameter threshold value based on an equation derived from a logistic regression analysis or neural network (classification) analysis.
The present disclosure provides a system, a method, and a computer program for testing used oil and, using the methodology described herein, and predicting (or enabling a user to predict) at, for example, 150 days of service, based on the used oil analysis, which units in, e.g., a railroad locomotive fleet should be changed at, for example, 184 days and which can safely continue to, for example, 276 days without an oil change.
According to a further aspect of the disclosure, a method is provided for selecting a plurality of engines for an extended lubricant drain interval, the method comprising: retrieving lubricant discard interval data for a plurality of engines; categorizing the lubricant discard data into at least two categories, including an extended lubricant discard interval category and a normal lubricant discard interval category; and generating a lubricant discard interval schedule for the plurality of engines. The extended lubricant discard interval category may, for example, comprise 276 days and a normal lubricant discard interval category comprises 184 days.
According to a still further aspect of the disclosure, a method is provided for predicting a lubricant drain interval in an engine based on an analysis parameter value that is measured in a sample of engine lubricant taken from the engine, the method comprising: receiving at a first input the analysis parameter value; receiving at a second input an analysis parameter threshold value; and predicting a future analysis parameter value based on the analysis parameter value and the analysis parameter threshold value.
According to a still further aspect of the disclosure, a computer readable medium may be provided that comprises a computer program, as described herein, for carrying out the process described herein.
Additional features, advantages, and embodiments of the disclosure may be set forth or apparent from consideration of the detailed description and drawings. Moreover, it is noted that the foregoing summary of the disclosure and the following detailed description and drawings provide non-limiting examples of the disclosure, which are intended to provide explanation without limiting the scope of the disclosure as claimed.
The present disclosure is further described in the detailed description that follows.